Intention to treat analysis
Intention-to-treat analysis is a statistical principle used in randomized controlled trials. It is based on the initial treatment intent, not on the treatment eventually administered. It is particularly useful in mitigating the effects of crossover and drop-out, which may break the random assignment to the treatment groups in a study.
Overview[edit | edit source]
The principle of intention-to-treat (ITT) analysis is to include all participants randomized regardless of whether they completed the study treatment or provided complete outcome data. This approach prevents bias caused by the loss of participants, which may disrupt the baseline equivalence established by randomization and which may reflect non-adherence, often related to prognosis or side effects.
Advantages[edit | edit source]
The main advantage of ITT analysis is its capacity to avoid overoptimistic estimates of the efficacy of an intervention resulting from the removal of non-compliant subjects or those who withdraw for any other reason.
Limitations[edit | edit source]
However, ITT analysis can also present limitations. For instance, it can underestimate the potential benefits of a treatment if there is a high rate of non-compliance or withdrawal.
See also[edit | edit source]
References[edit | edit source]
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